DeepBrain Chain project, AI bot that challenges humans, usql v0.6.0, and more in today’s top stories around machine learning, deep learning,and data science news.
1. DeepBrain Chain, the First AI Computing Platform Driven by Blockchain
DeepBrain Chain, is the first AI computing platform driven by blockchain for global AI computing resource sharing and scheduling. As most organizations do not have capital to buy expensive GPU servers, these companies provide a huge number of GPU servers which are unused or idle for a prolonged period.
The DeepBrain Chain provides a decentralized AI Computing platform, which is low cost, private, flexible, and safe. It serves the interests of several parties such as, the Miner’s main income is rewarded with token from mining, the AI companies just pay small amounts to run. Also, the Chain uses the smart contract in order to physically separate the data provider and data trainer. Thus, it protects the data of the provider. The interests of three major parties can be reconciled with the advanced technology. It is also automatically adjustable; if some nodes of DBC are attacked by hackers, the remaining nodes are working well as usual. DBC makes sure AI factories’ operations will never be interrupted.
2. Alibaba develops an AI bot to challenge humans in comprehension
Alibaba, China’s biggest online e-commerce, has developed a deep neural network model, which has out-performed humans in a global reading comprehension test. According to a release, the model has scored higher on the Stanford Question Answering dataset (a large-scale reading comprehension test with more than 10,000 questions).
Alibaba’s machine-learning models scored 82.44 on the test, compared with 82.304 by humans, on 11th January. Si Luo, chief scientist of natural language processing at Alibaba’s research arm, said that, “We believe the underlying technology can be gradually applied to numerous applications such as customer service, museum tutorials, and online response to inquiries from patients, freeing up human efforts in an unprecedented way”.
Similar to the model’s performance in the Stanford test, the machine learning model could identify the questions raised by consumers and look for the most relevant answers from prepared documents. Currently, the system only works best with questions that offer clear-cut answers. If the language or expressions are too vague, has grammatical errors, or there is no prepared answer, the bot may not work properly.
A universal command-line interface for SQL databases releases its version 0.6.0 with major updates below.
- Syntax highlighting
- Better compatibility with psql commands
- Homebrew support
The release also includes some minor feature additions and a general code cleanup.
Know more about this release on GitHub.
4. Cumulative Update #3 for SQL Server 2017 RTM
Microsoft has released the 3rd cumulative update for SQL Server 2017 RTM. The major changes include:
- CPU timeout setting added to Resource Governor workgroup
- Support for MAXDOP option added for CREATE STATISTICS and UPDATE STATISTICS statements in SQL Server 2017
- Improvement in tempdb spill diagnostics in DMV and Extended Events in SQL Server 2017
- XML Showplans can now provide a list of statistics used during query optimization in SQL Server 2017
- PolyBase technology enabled in SQL Server 2017
- Execution statistics of a scalar-valued, user-defined function added to the Showplan XML file in SQL Server 2017
- Optimizer row goal information added in query execution plans in SQL Server 2017
Other fixes and updates can be found here. The update can be downloaded from the Microsoft Download Center. Registration is no longer required to download the Cumulative updates.
5. Logz.io: AI-Powered ELK as a Service
Logz.io have launched an AI powered ELK as a cloud service solution which offers a fully managed environment and unlimited data with automatic data parsing capabilities. The ELK stack (for Elasticsearch, Logstash, and Kibana — now called the Elastic Stack) is basically used to handle operational data, specifically log files. Although open source, this stack can be hard to implement and manage according to enterprise standard and is often expensive due to its labor-intensive nature. Logz.io’s ELK as a cloud service solution is an enhanced architecture which delivers the advanced log analytics, integration and security that enterprises require. The platform has an ‘intelligence layer’ which applies artificial intelligence to optimize data, establish correlations between new deployments and resulting log errors, and identify undetected patterns in the data, among other uses.